OverlapNet: Loop Closing for LiDAR-based SLAM


Abstract: "Simultaneous localization and mapping (SLAM) is a fundamental capability required by most autonomous systems. In this paper, we address the problem of loop closing for SLAM based on 3D laser scans recorded by autonomous cars. Our approach utilizes a deep neural network exploiting different cues generated from LiDAR data for finding loop closures. It estimates an image overlap gene... » read more

Radar For Automotive: Why Do We Need Radar?


Communications and sensing technologies have transformed the automotive industry. More and more, cars include features and systems to interact with their environment, gaining awareness of the surrounding space, networking with each other and with the infrastructure, and detecting possible sources of danger. We can consider that vehicles have acquired their own “senses”: they know where they... » read more

ADAS: MIPI Is Key


Building on the enormous design and manufacturing base which made high-resolution, miniaturized digital cameras possible for mobile phones, the universe of MIPI applications has expanded to the automotive world. Today’s cars, particularly with the increasing sophistication of Advanced Driver Assistance Systems (ADAS), are brimming with cameras, sensors, and displays. Park assist, driver monit... » read more

Enhancement of Robustness in Object Detection Module for Advanced Driver Assistance Systems


Abstract: "A unified system integrating a compact object detector and a surrounding environmental condition classifier for enhancing the robustness of object detection scheme in advanced driver assistance systems (ADAS) is proposed in this paper. ADAS are invented to improve traffic safety and effectiveness in autonomous driving systems where object detection plays an extremely important rol... » read more

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving


Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to perform detection and prediction tasks. We extend the BEV network ... » read more

Research on quantum cognition in autonomous driving


Abstract "Autonomous vehicles for the intention of human behavior of the estimated traffic participants and their interaction is the main problem in automatic driving system. Classical cognitive theory assumes that the behavior of human traffic participants is completely reasonable when studying estimation of intention and interaction. However, according to the quantum cognition and ... » read more

How Semiconductor Solutions Address Safety Requirements Of Future Power Distribution Networks In Autonomous Vehicles


Open up the bonnet of any modern automobile and many of us would be hard-pressed to find anything that we could fix ourselves. With pipes and cables almost artistically integrated into the engine bay, and sleek plastic covers fitted everywhere, there is very little that can still be recognized, yet alone repaired. Perhaps the only location where we feel comfortable is the “fuse box”, or pow... » read more

Physics-Based Sensor Validation Via Ansys: Driving New Automotive Innovations


Autonomous driving is revolutionizing the global automotive industry. With every new model, cars are smarter and more capable of independently responding to external signals like lane markings, highway signs, other cars and pedestrians. However, formulating a correct response via artificial intelligence depends on flawless sensor performance. With so many sensors supporting the advanced driv... » read more

Changes In Auto Architectures


Automotive architectures are changing from a driver-centric model to one where technology supplements and in some cases replaces the driver. Hans Adlkofer, senior vice president and head of the Automotive Systems Group at Infineon, looks at the different levels of automation in a vehicle, what’s involved in the shift from domain to zonal architectures, why a mix of processors will be required... » read more

Automotive Innovations In Semiconductors


By Jeff Barnum, Janay Camp, and Cathy Perry Sullivan The semiconductor industry performed better than expected in 2020 despite the impact of COVID-19 on the global economy and is preparing for accelerated growth in 2021 and beyond. The global coronavirus pandemic significantly increased demand for communications electronics and fueled the growth in cloud computing to support remote work and ... » read more

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